DOI: 10.1016/j.jag.2016.12.007
Scopus记录号: 2-s2.0-85032455571
论文题名: Integrating age in the detection and mapping of incongruous patches in coffee (Coffea arabica) plantations using multi-temporal Landsat 8 NDVI anomalies
作者: Chemura A ; , Mutanga O ; , Dube T
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2017
卷: 57 起始页码: 1
结束页码: 13
语种: 英语
英文关键词: Age
; Coffee
; Crop condition
; Monitoring
; Multi-temporal landsat NDVI
Scopus关键词: accuracy assessment
; coffee
; detection method
; Landsat
; mapping
; monitoring
; NDVI
; plantation
; Coffea arabica
英文摘要: The development of cost-effective, reliable and easy to implement crop condition monitoring methods is urgently required for perennial tree crops such as coffee (Coffea arabica), as they are grown over large areas and represent long term and higher levels of investment. These monitoring methods are useful in identifying farm areas that experience poor crop growth, pest infestation, diseases outbreaks and/or to monitor response to management interventions. This study compares field level coffee mean NDVI and LSWI anomalies and age-adjusted coffee mean NDVI and LSWI anomalies in identifying and mapping incongruous patches across perennial coffee plantations. To achieve this objective, we first derived deviation of coffee pixels from the global coffee mean NDVI and LSWI values of nine sequential Landsat 8 OLI image scenes. We then evaluated the influence of coffee age class (young, mature and old) on Landsat-scale NDVI and LSWI values using a one-way ANOVA and since results showed significant differences, we adjusted NDVI and LSWI anomalies for age-class. We then used the cumulative inverse distribution function (α ≤ 0.05) to identify fields and within field areas with excessive deviation of NDVI and LSWI from the global and the age-expected mean for each of the Landsat 8 OLI scene dates spanning three seasons. Results from accuracy assessment indicated that it was possible to separate incongruous and healthy patches using these anomalies and that using NDVI performed better than using LSWI for both global and age-adjusted mean anomalies. Using the age-adjusted anomalies performed better in separating incongruous and healthy patches than using the global mean for both NDVI (Overall accuracy = 80.9% and 68.1% respectively) and for LSWI (Overall accuracy = 68.1% and 48.9% respectively). When applied to other Landsat 8 OLI scenes, the results showed that the proportions of coffee fields that were modelled incongruent decreased with time for the young age category and while it increased for the mature and old age classes with time. We concluded that the method could be useful for the identification of anomalous patches using Landsat scale time series data to monitor large coffee plantations and provide an indication of areas requiring particular field attention. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79927
Appears in Collections: 气候变化事实与影响
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作者单位: University of KwaZulu-Natal, School of Agricultural, Earth & Environmental Sciences, Geography Department, P/Bag X01, Scottsville, Pietermaritzburg, South Africa; Environmental Science and Technology Department, Chinhoyi University of Technology, P/Bag 7724, Chinhoyi, Zimbabwe; Department of Geography & Environmental Studies, University of Limpopo, P/Bag X1106, Sovenga 0727, Polokwane, South Africa
Recommended Citation:
Chemura A,, Mutanga O,, Dube T. Integrating age in the detection and mapping of incongruous patches in coffee (Coffea arabica) plantations using multi-temporal Landsat 8 NDVI anomalies[J]. International Journal of Applied Earth Observation and Geoinformation,2017-01-01,57